Triple

T6472528
Position Surface form Disambiguated ID Type / Status
Subject Gouwzee E145988 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Monnickendam E203525 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Monnickendam | Statement: [Gouwzee, hasNearbySettlement, Monnickendam]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monnickendam
Context triple: [Gouwzee, hasNearbySettlement, Monnickendam]
  • A. Monnickendam chosen
    Monnickendam is a historic fishing town in North Holland, Netherlands, known for its well-preserved old harbor and traditional Dutch architecture.
  • B. Nieuwendam
    Nieuwendam is a historic neighborhood in the northern part of Amsterdam, known for its former village character and waterfront location along the IJ.
  • C. Onderdendam
    Onderdendam is a small historic village in the Dutch province of Groningen, known for its canals, bridges, and traditional architecture.
  • D. Heinkenszand
    Heinkenszand is a village in the Dutch province of Zeeland that serves as a local center within the South Beveland region.
  • E. Vechta
    Vechta is a town in Lower Saxony, Germany, known for its historical significance, university, and annual Stoppelmarkt fair.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c008fec7408190af7b146dc63d9750 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a3188488190a1b7452ede91ba5e completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9493bf8088190bc59dd0e36d16a20 completed March 29, 2026, 3:46 p.m.
Created at: March 22, 2026, 4:50 p.m.